Civil & Environmental Engr: AI for Water Resources (B)

About CEE 5990 B

See Schedule of Courses for specific titles.

Notes

Open to degree and PACE students

Section Description

Examines how artificial intelligence and machine learning are changing hydrologic prediction and water-resources decision making. Students evaluate applications in streamflow and flood forecasting, weather inputs to hydrologic models, evapotranspiration and irrigation, groundwater, water quality, urban systems, and reservoir operations. Emphasis is placed on water-data limitations, rigorous validation, uncertainty, physics-guided learning, reproducibility, operational readiness, and responsible deployment. Tuesdays feature framing lectures, several with instructor-run notebooks using real water data; most Thursdays feature seminars on research literature. A team project culminates in an end-of-semester symposium.

Section Expectation

Prerequisite: graduate standing and prior coursework in hydrology, hydraulics, or water resources, or instructor permission. Basic statistics is assumed; Python experience is recommended but not required. Advanced undergraduates may enroll with instructor permission. Coursework includes assigned readings and short memos before seminars, three applied studies, and a team project.

Important Dates

Note: These dates may change before registration begins.

Courses may be cancelled due to low enrollment. Show your interest by enrolling.

Resources

• Parking
• PACE Course Pricing
• Textbooks

Other Sections